Description: Current vaccines do not provide sufficient levels of protection against divergent porcine reproductive and respiratory syndrome virus (PRRSV) strains circulating in the field, mainly due to the substantial variation of the viral genome. We describe here a novel approach to generate a PRRSV vaccine candidate that could confer unprecedented levels of heterologous protection against divergent PRRSV isolates. By using a set of 59 nonredundant, full-genome sequences of type 2 PRRSVs, a consensus genome (designated PRRSV-CON) was generated by aligning these 59 PRRSV full-genome sequences, followed by selecting the most common nucleotide found at each position of the alignment. Next, the synthetic PRRSV-CON strain was generated through the use of reverse genetics. PRRSV-CON replicates as efficiently as our prototype PRRSV strain FL12, both in vitro and in vivo . Importantly, when inoculated into pigs, PRRSV-CON confers significantly broader levels of heterologous protection than does wild-type PRRSV. Collectively, our data demonstrate that PRRSV-CON can serve as an excellent candidate for the development of a broadly protective PRRSV vaccine. IMPORTANCE The extraordinary genetic variation of RNA viruses poses a monumental challenge for the development of broadly protective vaccines against these viruses. To minimize the genetic dissimilarity between vaccine immunogens and contemporary circulating viruses, computational strategies have been developed for the generation of artificial immunogen sequences (so-called "centralized" sequences) that have equal genetic distances to the circulating viruses. Thus far, the generation of centralized vaccine immunogens has been carried out at the level of individual viral proteins. We expand this concept to PRRSV, a highly variable RNA virus, by creating a synthetic PRRSV strain based on a centralized PRRSV genome sequence. This study provides the first example of centralizing the whole genome of an RNA virus to improve vaccine coverage. This concept may be significant for the development of vaccines against genetically variable viruses that require active viral replication in order to achieve complete immune protection.

Description: Motivation: The extraordinary genetic and antigenic variability of RNA viruses is arguably the greatest challenge to the development of broadly effective vaccines. No single viral variant can induce sufficiently broad immunity, and incorporating all known naturally circulating variants into one multivalent vaccine is not feasible. Furthermore, no objective strategies currently exist to select actual viral variants that should be included or excluded in polyvalent vaccines. Results: To address this problem, we demonstrate a method based on graph theory that quantifies the relative importance of viral variants. We demonstrate our method through application to the envelope glycoprotein gene of a particularly diverse RNA virus of pigs: porcine reproductive and respiratory syndrome virus (PRRSV). Using distance matrices derived from sequence nucleotide difference, amino acid difference and evolutionary distance, we constructed viral networks and used common network statistics to assign each sequence an objective ranking of relative ‘importance’. To validate our approach, we use an independent published algorithm to score our top-ranked wild-type variants for coverage of putative T-cell epitopes across the 9383 sequences in our dataset. Top-ranked viruses achieve significantly higher coverage than low-ranked viruses, and top-ranked viruses achieve nearly equal coverage as a synthetic mosaic protein constructed in silico from the same set of 9383 sequences. Conclusion: Our approach relies on the network structure of PRRSV but applies to any diverse RNA virus because it identifies subsets of viral variants that are most important to overall viral diversity. We suggest that this method, through the objective quantification of variant importance, provides criteria for choosing viral variants for further characterization, diagnostics, surveillance and ultimately polyvalent vaccine development. Contact: tgoldberg@vetmed.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online.